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    Regarding “Computer-Extracted Texture Features to Distinguish Cerebral Radionecrosis from Recurrent Brain Tumors on Multiparametric MRI: A Feasibility Study” | American Journal of Neuroradiology  
    

















    





























    
  
  




    
    

  

      


    

      

  
  
  

    

  

    

  

                
    

      

  

    

  
      
  
  

    


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Letter

  
      

  
      
Regarding “Computer-Extracted Texture Features to Distinguish Cerebral Radionecrosis from Recurrent Brain Tumors on Multiparametric MRI: A Feasibility Study”
  
    	
A.D. Schweitzer, G.C. Chiang, J. Ivanidze, H. Baradaran, R.J. Young and R.D. Zimmerman

  
    	
American Journal of Neuroradiology March 2017,  38 (3) E18-E19; DOI: https://doi.org/10.3174/ajnr.A5019 

  
  
  



  


  
  



			

		

	
	
 	
	  
  

		
		

			

			  

  
      
  
  

    
  


  
  



  
      
  
  

    

  

    

  
      
  
  

    
References
  1. 1.↵
    1. 

    2. Tiwari  P, 
    3. Prasanna  P, 
    4. Wolansky  L, et al
    . Computer-extracted texture features to distinguish cerebral radionecrosis from recurrent brain tumors on multiparametric MRI: a feasibility study. AJNR Am J Neuroradiol 2016 
Sep 
15. [Epub ahead of print] doi:10.3174/ajnr.A4931 pmid:27633806
    Abstract/FREE Full Text
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    2. Yun  TJ, 
    3. Park  CK, 
    4. Kim  TM, et al
    . Glioblastoma treated with concurrent radiation therapy and temozolomide chemotherapy: differentiation of true progression from pseudoprogression with quantitative dynamic contrast-enhanced MR imaging. Radiology 2015;274:830–40 doi:10.1148/radiol.14132632 pmid:25333475
    CrossRefPubMed
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    2. Thomas  AA, 
    3. Arevalo-Perez  J, 
    4. Kaley  T, et al
    . Dynamic contrast enhanced T1 MRI perfusion differentiates pseudoprogression from recurrent glioblastoma. J Neurooncol 2015;125:183–90 doi:10.1007/s11060-015-1893-z pmid:26275367
    CrossRefPubMed
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    2. Hatzoglou  V, 
    3. Yang  TJ, 
    4. Omuro  A, et al
    . A prospective trial of dynamic contrast-enhanced MRI perfusion and fluorine-18 FDG PET-CT in differentiating brain tumor progression from radiation injury after cranial irradiation. Neuro Oncol 2016;18:873–80 doi:10.1093/neuonc/nov301 pmid:26688076
    Abstract/FREE Full Text
  5. 5.↵
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    2. Patel  P, 
    3. Baradaran  H, 
    4. Delgado  D, et al
    . MR perfusion-weighted imaging in the evaluation of high-grade gliomas after treatment: a systematic review and meta-analysis. Neuro Oncol 2016 
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    2. Chiang  GC, 
    3. Galla  N, 
    4. Ferraro  R, et al
    . The added prognostic value of metabolic tumor size on FDG-PET at first suspected recurrence of glioblastoma multiforme. J Neuroimaging 2016 
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  7. 7.↵
    @TheASNR. https://twitter.com/TheASNR/status/777889433022558208. Posted September 19, 2016
  


  
  



  




  


  
  



  
      
  
  

    
  


  
  



  
      
  
  

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Regarding “Computer-Extracted Texture Features to Distinguish Cerebral Radionecrosis from Recurrent Brain Tumors on Multiparametric MRI: A Feasibility Study”
  
    	
A.D. Schweitzer, G.C. Chiang, J. Ivanidze, H. Baradaran, R.J. Young, R.D. Zimmerman

  
    	
American Journal of Neuroradiology Mar 2017, 38 (3) E18-E19; DOI: 10.3174/ajnr.A5019 

  
  
  



  


  
  



  
      
  
  

    

  
    
  
  
    
  
  
    
  


  


  
  



  
      
  
  

    
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